Antarctica - ASV analysis

Get the Antarctica ASVs

set id description
16 Antar_2015_18S_V4
17 Antar_2015_16S_plastid
18 Antar_2015_18S_V4_sorted
  • Only use asv for which supergroup_boot >= 90
  • Only keep photosynthetic groups abd exclude dinoflagellates
Phyloseq - 18S filter
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 707 taxa and 123 samples ]
sample_data() Sample Data:       [ 123 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 707 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 16S plastid
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 419 taxa and 103 samples ]
sample_data() Sample Data:       [ 103 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 419 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 18S sort
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 264 taxa and 60 samples ]
sample_data() Sample Data:       [ 60 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 264 taxa by 8 taxonomic ranks ]
============================
 [1] "sample_id"                      "file_name"                     
 [3] "sample_name"                    "sample_code"                   
 [5] "metadata_code"                  "replicate"                     
 [7] "DNA_RNA"                        "fraction_name"                 
 [9] "fraction_min"                   "fraction_max"                  
[11] "sample_concentration"           "sample_sorted"                 
[13] "reads_total"                    "sample_remark"                 
[15] "metadata_id"                    "metadata_code_original"        
[17] "project"                        "cruise"                        
[19] "station_id"                     "station_id_num"                
[21] "year"                           "date"                          
[23] "time"                           "season"                        
[25] "depth_level"                    "depth"                         
[27] "substrate"                      "substrate_description"         
[29] "substrate_description_detailed" "experiment_name"               
[31] "experiment_time"                "experiment_time_unit"          
[33] "experiment_bottle"              "experiment_condition"          
[35] "latitude"                       "longitude"                     
[37] "site_name"                      "country"                       
[39] "oceanic_region"                 "bottom_depth"                  
[41] "temperature"                    "salinity"                      
[43] "pH"                             "O2"                            
[45] "fluorescence"                   "ice_coverage"                  
[47] "Chla"                           "NO2"                           
[49] "NO3"                            "PO4"                           
[51] "Si"                             "Chla_0.2_3 um"                 
[53] "bact_ml"                        "syn_ml"                        
[55] "peuk_ml"                        "neuk_ml"                       
[57] "crypto_ml"                      "virus_small_ml"                
[59] "virus_large_ml"                 "metadata_remark"               
[61] "sample_label"                  

Get the different fraction separately

Phyloseq - 18S filter 0.2 um
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 331 taxa and 43 samples ]
sample_data() Sample Data:       [ 43 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 331 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 18S filter 3 um
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 377 taxa and 44 samples ]
sample_data() Sample Data:       [ 44 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 377 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 18S filter 20 um
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 310 taxa and 36 samples ]
sample_data() Sample Data:       [ 36 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 310 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 16S plastid 0.2 um
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 183 taxa and 29 samples ]
sample_data() Sample Data:       [ 29 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 183 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 16S plastid 3 um
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 219 taxa and 42 samples ]
sample_data() Sample Data:       [ 42 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 219 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 16S plastid 20 um
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 212 taxa and 32 samples ]
sample_data() Sample Data:       [ 32 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 212 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 18S sort pico
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 185 taxa and 30 samples ]
sample_data() Sample Data:       [ 30 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 185 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 18S sort nano
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 132 taxa and 30 samples ]
sample_data() Sample Data:       [ 30 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 132 taxa by 8 taxonomic ranks ]
============================

Surface samples

  • Only use Station 6 (not 14)
  • Only surface considered (5 m)
  • Do not consider TFF samples
  • Very important, must remove taxa that are not present in the filtered samples
Phyloseq - 18S filter surface
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 394 taxa and 50 samples ]
sample_data() Sample Data:       [ 50 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 394 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 16S plastid surface
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 236 taxa and 40 samples ]
sample_data() Sample Data:       [ 40 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 236 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 18S sort surface
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 114 taxa and 16 samples ]
sample_data() Sample Data:       [ 16 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 114 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 18S filter 0.2 um surface
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 196 taxa and 17 samples ]
sample_data() Sample Data:       [ 17 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 196 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 18S filter 3 um surface
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 229 taxa and 18 samples ]
sample_data() Sample Data:       [ 18 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 229 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 18S filter 20 um surface
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 201 taxa and 15 samples ]
sample_data() Sample Data:       [ 15 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 201 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 16S plastid 0.2 um surface
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 112 taxa and 11 samples ]
sample_data() Sample Data:       [ 11 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 112 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 16S plastid 3 um surface
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 142 taxa and 16 samples ]
sample_data() Sample Data:       [ 16 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 142 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 16S plastid 20 um surface
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 120 taxa and 13 samples ]
sample_data() Sample Data:       [ 13 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 120 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 18S sort pico surface
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 65 taxa and 8 samples ]
sample_data() Sample Data:       [ 8 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 65 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 18S sort nano surface
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 70 taxa and 8 samples ]
sample_data() Sample Data:       [ 8 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 70 taxa by 8 taxonomic ranks ]
============================

Normalize and transform to long form

18S filter surface
============================
========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 394 taxa and 50 samples ]
sample_data() Sample Data:       [ 50 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 394 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  23202
16S plastid surface
============================
========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 236 taxa and 40 samples ]
sample_data() Sample Data:       [ 40 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 236 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  28885
18S sort surface
============================
========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 114 taxa and 16 samples ]
sample_data() Sample Data:       [ 16 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 114 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  27275
18S filter 0.2 um surface
============================
========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 196 taxa and 17 samples ]
sample_data() Sample Data:       [ 17 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 196 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  14647
18S filter 3 um surface
============================
========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 229 taxa and 18 samples ]
sample_data() Sample Data:       [ 18 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 229 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  24783
18S filter 20 um surface
============================
========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 201 taxa and 15 samples ]
sample_data() Sample Data:       [ 15 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 201 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  29427
16S plastid 0.2 um surface
============================
========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 112 taxa and 11 samples ]
sample_data() Sample Data:       [ 11 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 112 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  28471
16S plastid 3 um surface
============================
========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 142 taxa and 16 samples ]
sample_data() Sample Data:       [ 16 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 142 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  31801
16S plastid 20 um surface
============================
========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 120 taxa and 13 samples ]
sample_data() Sample Data:       [ 13 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 120 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  25641
18S sort pico surface
============================
========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 65 taxa and 8 samples ]
sample_data() Sample Data:       [ 8 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 65 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  33258
18S sort nano surface
============================
========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 70 taxa and 8 samples ]
sample_data() Sample Data:       [ 8 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 70 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  21650

List of classes

division class
Chlorophyta Chlorophyceae
Chlorophyta Mamiellophyceae
Chlorophyta Palmophyllophyceae
Chlorophyta Prasino-Clade-V
Chlorophyta Pyramimonadophyceae
Chlorophyta Trebouxiophyceae
Chlorophyta Ulvophyceae
Cryptophyta Cryptophyceae
Haptophyta Prymnesiophyceae
Ochrophyta Bacillariophyta
Ochrophyta Bolidophyceae
Ochrophyta Chrysophyceae
Ochrophyta Dictyochophyceae
Ochrophyta MOCH-1
Ochrophyta MOCH-2
Ochrophyta Pelagophyceae
Ochrophyta Phaeophyceae
Ochrophyta Xanthophyceae
Rhodophyta Bangiophyceae
Rhodophyta Florideophyceae

Heatmaps

Filter : Dictyo / Chrysophyceae /Pelago /Bacili / Crypto / Pyrami / Mamiello

Class

Most abundant 10%


========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 7 taxa and 17 samples ]
sample_data() Sample Data:       [ 17 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 7 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  13808


========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 7 taxa and 18 samples ]
sample_data() Sample Data:       [ 18 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 7 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  23366


========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 5 taxa and 15 samples ]
sample_data() Sample Data:       [ 15 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 5 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  27860


========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 4 taxa and 11 samples ]
sample_data() Sample Data:       [ 11 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 4 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  27592


========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 5 taxa and 16 samples ]
sample_data() Sample Data:       [ 16 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 5 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  31460


========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 4 taxa and 13 samples ]
sample_data() Sample Data:       [ 13 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 4 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  24881


========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 4 taxa and 8 samples ]
sample_data() Sample Data:       [ 8 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 4 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  32016


========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 4 taxa and 8 samples ]
sample_data() Sample Data:       [ 8 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 4 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  21054

#### Selected

Species

Most abundant


========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 11 taxa and 17 samples ]
sample_data() Sample Data:       [ 17 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 11 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  11704


========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 8 taxa and 18 samples ]
sample_data() Sample Data:       [ 18 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 8 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  20196


========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 11 taxa and 15 samples ]
sample_data() Sample Data:       [ 15 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 11 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  26302


========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 5 taxa and 11 samples ]
sample_data() Sample Data:       [ 11 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 5 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  27286


========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 8 taxa and 16 samples ]
sample_data() Sample Data:       [ 16 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 8 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  30697


========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 6 taxa and 13 samples ]
sample_data() Sample Data:       [ 13 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 6 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  24093


========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 5 taxa and 8 samples ]
sample_data() Sample Data:       [ 8 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 5 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  28373


========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 6 taxa and 8 samples ]
sample_data() Sample Data:       [ 8 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 6 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  19513

### Selected

species_selected <- c("Thalassiosira_minima", "Fragilariopsis_cylindrus", "Minidiscus_sp.", 
    "Chaetoceros_neogracilis", "Porosira_glacialis", "Coretrhon_inerme", "Palmaria_palmata", 
    "Pseudo-nitzchia_seriata", "Micromonas_polaris", "Micromonas_clade_B3", 
    "Bathycoccus_prasinos", "Pyramimonas_gelidicola", "Geminigera_cryophila", 
    "Pelagophyceae_XXX_sp.", "Phaeocystis_antarctica")

heatmap_species_selected <- list()

for (one_sample_type in sample_type_surface[4:11]) {
    
    ps_heat <- tax_glom(ps[[one_sample_type]], taxrank = "species") %>% subset_taxa(species %in% 
        species_selected)
    
    # Try to order by division and species...  tax_table <-
    # data.frame(tax_table(ps_heat)@.Data) taxa_names(ps_heat) <-
    # str_c(tax_table$division, tax_table$species, sep=' - ')
    
    gg <- plot_heatmap(ps_heat, method = "NMDS", distance = "bray", taxa.label = "species", 
        taxa.order = "class", sample.label = "sample_label", sample.order = "sample_label", 
        low = "beige", high = "red", na.value = "gray95", trans = NULL, title = one_sample_type) + 
        xlab("") + ylab("") + theme(axis.text.x = element_text(angle = 45, hjust = 1, 
        vjust = 1)) + scale_fill_gradient(limits = c(0, 20000), low = "beige", 
        high = "red", na.value = "gray95")
    
    if (str_detect(one_sample_type, "18S filter 0.2")) 
        gg <- gg + geom_vline(xintercept = c(6.5, 9.5, 12.5))
    
    if (one_sample_type == "18S filter 3 um surface") 
        gg <- gg + geom_vline(xintercept = c(8.5, 10.5, 13.5))
    
    if (one_sample_type == "18S filter 20 um surface") 
        gg <- gg + geom_vline(xintercept = c(8.5, 9.5))
    
    
    
    # plot(heatmap(otu_table(ps_heat))) , trans = scales::log_trans(10)
    
    print(gg)
    
    heatmap_species_selected[[one_sample_type]] <- gg
    
}

# NMDS

Apply to all samples

Square root transformation
Wisconsin double standardization
Run 0 stress 0.1687566 
Run 1 stress 0.1687634 
... Procrustes: rmse 0.002985303  max resid 0.01690689 
Run 2 stress 0.1687197 
... New best solution
... Procrustes: rmse 0.002431247  max resid 0.01134347 
Run 3 stress 0.1733998 
Run 4 stress 0.1739068 
Run 5 stress 0.1766939 
Run 6 stress 0.1687159 
... New best solution
... Procrustes: rmse 0.001111716  max resid 0.005731252 
... Similar to previous best
Run 7 stress 0.1733984 
Run 8 stress 0.1739071 
Run 9 stress 0.1746154 
Run 10 stress 0.1835842 
Run 11 stress 0.168719 
... Procrustes: rmse 0.001095126  max resid 0.005701493 
... Similar to previous best
Run 12 stress 0.1835529 
Run 13 stress 0.168719 
... Procrustes: rmse 0.001110988  max resid 0.005739634 
... Similar to previous best
Run 14 stress 0.168719 
... Procrustes: rmse 0.001112726  max resid 0.005733226 
... Similar to previous best
Run 15 stress 0.1733994 
Run 16 stress 0.1745761 
Run 17 stress 0.1721531 
Run 18 stress 0.1734118 
Run 19 stress 0.1872138 
Run 20 stress 0.1687632 
... Procrustes: rmse 0.003837324  max resid 0.01748068 
*** Solution reached
[1] 3

Call:
metaMDS(comm = veganifyOTU(physeq), distance = distance) 

global Multidimensional Scaling using monoMDS

Data:     wisconsin(sqrt(veganifyOTU(physeq))) 
Distance: bray 

Dimensions: 2 
Stress:     0.1687159 
Stress type 1, weak ties
Two convergent solutions found after 20 tries
Scaling: centring, PC rotation, halfchange scaling 
Species: expanded scores based on 'wisconsin(sqrt(veganifyOTU(physeq)))' 

Square root transformation
Wisconsin double standardization
Run 0 stress 0.1492484 
Run 1 stress 0.1492468 
... New best solution
... Procrustes: rmse 0.0002507616  max resid 0.001358323 
... Similar to previous best
Run 2 stress 0.1489429 
... New best solution
... Procrustes: rmse 0.01404688  max resid 0.06477591 
Run 3 stress 0.1732926 
Run 4 stress 0.1489447 
... Procrustes: rmse 0.0005970766  max resid 0.003273668 
... Similar to previous best
Run 5 stress 0.1526353 
Run 6 stress 0.1489494 
... Procrustes: rmse 0.001870841  max resid 0.01026137 
Run 7 stress 0.1489076 
... New best solution
... Procrustes: rmse 0.005462155  max resid 0.02114027 
Run 8 stress 0.1489094 
... Procrustes: rmse 0.0002241435  max resid 0.00122347 
... Similar to previous best
Run 9 stress 0.1931313 
Run 10 stress 0.1526371 
Run 11 stress 0.1669089 
Run 12 stress 0.2018991 
Run 13 stress 0.188055 
Run 14 stress 0.1526361 
Run 15 stress 0.1547389 
Run 16 stress 0.1760578 
Run 17 stress 0.1762028 
Run 18 stress 0.1965688 
Run 19 stress 0.1755688 
Run 20 stress 0.1870225 
*** Solution reached
[1] 3

Call:
metaMDS(comm = veganifyOTU(physeq), distance = distance) 

global Multidimensional Scaling using monoMDS

Data:     wisconsin(sqrt(veganifyOTU(physeq))) 
Distance: bray 

Dimensions: 2 
Stress:     0.1489076 
Stress type 1, weak ties
Two convergent solutions found after 20 tries
Scaling: centring, PC rotation, halfchange scaling 
Species: expanded scores based on 'wisconsin(sqrt(veganifyOTU(physeq)))' 

Square root transformation
Wisconsin double standardization
Run 0 stress 0.05090316 
Run 1 stress 0.05736207 
Run 2 stress 0.05090323 
... Procrustes: rmse 0.0001234125  max resid 0.0002263345 
... Similar to previous best
Run 3 stress 0.05185334 
Run 4 stress 0.05090317 
... Procrustes: rmse 3.166825e-05  max resid 5.733514e-05 
... Similar to previous best
Run 5 stress 0.05090316 
... Procrustes: rmse 3.131882e-05  max resid 5.132691e-05 
... Similar to previous best
Run 6 stress 0.05161249 
Run 7 stress 0.0520288 
Run 8 stress 0.05379784 
Run 9 stress 0.05723174 
Run 10 stress 0.05161249 
Run 11 stress 0.05379785 
Run 12 stress 0.05220006 
Run 13 stress 0.05940653 
Run 14 stress 0.05533946 
Run 15 stress 0.05344022 
Run 16 stress 0.05220002 
Run 17 stress 0.05161251 
Run 18 stress 0.05379788 
Run 19 stress 0.05161248 
Run 20 stress 0.0520288 
*** Solution reached
[1] 3

Call:
metaMDS(comm = veganifyOTU(physeq), distance = distance) 

global Multidimensional Scaling using monoMDS

Data:     wisconsin(sqrt(veganifyOTU(physeq))) 
Distance: bray 

Dimensions: 2 
Stress:     0.05090316 
Stress type 1, weak ties
Two convergent solutions found after 20 tries
Scaling: centring, PC rotation, halfchange scaling 
Species: expanded scores based on 'wisconsin(sqrt(veganifyOTU(physeq)))' 

Vertical profile

  • Station 6 - 2015-01-16
  • Very important, must remove taxa that are not present in the filtered samples
  • Do not use the TFF

Filter the data


========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 175 taxa and 15 samples ]
sample_data() Sample Data:       [ 15 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 175 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  43491Phyloseq - 18S filter profile
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 175 taxa and 15 samples ]
sample_data() Sample Data:       [ 15 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 175 taxa by 8 taxonomic ranks ]
============================

========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 107 taxa and 15 samples ]
sample_data() Sample Data:       [ 15 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 107 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  41130Phyloseq - 16S plastid profile
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 107 taxa and 15 samples ]
sample_data() Sample Data:       [ 15 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 107 taxa by 8 taxonomic ranks ]
============================

========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 96 taxa and 10 samples ]
sample_data() Sample Data:       [ 10 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 96 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  29305Phyloseq - 18S sort profile
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 96 taxa and 10 samples ]
sample_data() Sample Data:       [ 10 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 96 taxa by 8 taxonomic ranks ]
============================

========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 92 taxa and 5 samples ]
sample_data() Sample Data:       [ 5 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 92 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  30265Phyloseq - 18S filter 0.2 um profile
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 92 taxa and 5 samples ]
sample_data() Sample Data:       [ 5 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 92 taxa by 8 taxonomic ranks ]
============================

========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 86 taxa and 5 samples ]
sample_data() Sample Data:       [ 5 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 86 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  31205Phyloseq - 18S filter 3 um profile
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 86 taxa and 5 samples ]
sample_data() Sample Data:       [ 5 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 86 taxa by 8 taxonomic ranks ]
============================

========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 121 taxa and 5 samples ]
sample_data() Sample Data:       [ 5 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 121 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  58797Phyloseq - 18S filter 20 um profile
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 121 taxa and 5 samples ]
sample_data() Sample Data:       [ 5 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 121 taxa by 8 taxonomic ranks ]
============================

========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 46 taxa and 5 samples ]
sample_data() Sample Data:       [ 5 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 46 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  40267Phyloseq - 16S plastid 0.2 um profile
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 46 taxa and 5 samples ]
sample_data() Sample Data:       [ 5 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 46 taxa by 8 taxonomic ranks ]
============================

========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 62 taxa and 5 samples ]
sample_data() Sample Data:       [ 5 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 62 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  46172Phyloseq - 16S plastid 3 um profile
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 62 taxa and 5 samples ]
sample_data() Sample Data:       [ 5 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 62 taxa by 8 taxonomic ranks ]
============================

========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 74 taxa and 5 samples ]
sample_data() Sample Data:       [ 5 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 74 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  47020Phyloseq - 16S plastid 20 um profile
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 74 taxa and 5 samples ]
sample_data() Sample Data:       [ 5 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 74 taxa by 8 taxonomic ranks ]
============================

========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 65 taxa and 5 samples ]
sample_data() Sample Data:       [ 5 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 65 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  29412Phyloseq - 18S sort pico profile
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 65 taxa and 5 samples ]
sample_data() Sample Data:       [ 5 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 65 taxa by 8 taxonomic ranks ]
============================

========== 
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 46 taxa and 5 samples ]
sample_data() Sample Data:       [ 5 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 46 taxa by 8 taxonomic ranks ]

==========
The median number of reads used for normalization is  28502Phyloseq - 18S sort nano profile
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 46 taxa and 5 samples ]
sample_data() Sample Data:       [ 5 samples by 61 sample variables ]
tax_table()   Taxonomy Table:    [ 46 taxa by 8 taxonomic ranks ]
============================

Compare the contributions of CLASS and GENUS using the different methods

Sample by sample comparison

  • Each dot corresponds to the relative contribution of the taxonomic level considered for a sample for which both 18S and 16S has been performed

Global comparison of genera found with the 3 methods

Compute table of number of samples for each genus (rows) vs the three methods (columns)

  • Only keep
    • 2015 samples because it is the only dataset for which we have the three types of samples
    • 0.2 and 3 um fractions (to be comparable with sorting)
  • Remove genera that contains _X
Class not found in one type of sample
18S filter
division class n_reads_18S_filter n_samples_18S_filter n_reads_16S_plastid n_samples_16S_plastid n_reads_18S_sort n_samples_18S_sort
Chlorophyta Prasino-Clade-V NA NA 0.404492 29 NA NA
18S sort
division class n_reads_18S_filter n_samples_18S_filter n_reads_16S_plastid n_samples_16S_plastid n_reads_18S_sort n_samples_18S_sort
Chlorophyta Trebouxiophyceae 0.0004002 3 0.0004331 3 NA NA
Rhodophyta Florideophyceae 0.0755969 29 0.0018921 10 NA NA
Chlorophyta Prasino-Clade-V NA NA 0.4044920 29 NA NA
16S filter
division class n_reads_18S_filter n_samples_18S_filter n_reads_16S_plastid n_samples_16S_plastid n_reads_18S_sort n_samples_18S_sort
Chlorophyta Ulvophyceae 0.0258306 24 NA NA 0.5714412 4
Ochrophyta MOCH-2 0.0334232 28 NA NA 0.0449041 11
Genera  found in the three types of samples
18S filter
division class order family genus n_reads_18S_filter n_samples_18S_filter n_reads_16S_plastid n_samples_16S_plastid n_reads_18S_sort n_samples_18S_sort
Chlorophyta Mamiellophyceae Mamiellales Bathycoccaceae Bathycoccus 0.2422204 32 0.0038980 3 1.1036274 23
Chlorophyta Mamiellophyceae Mamiellales Mamiellaceae Mantoniella 0.0004829 1 0.0559522 24 0.0013399 1
Chlorophyta Palmophyllophyceae Prasinococcales Prasinococcales-Clade-B Prasinoderma 0.0302120 31 0.0200905 24 0.0113499 2
Chlorophyta Pyramimonadophyceae Pyramimonadales Pyramimonadaceae Pyramimonas 0.6251602 35 4.9393080 30 2.3116630 23
Cryptophyta Cryptophyceae Cryptomonadales Cryptomonadales_X Geminigera 8.7159220 35 0.0000594 1 5.9759821 30
Haptophyta Prymnesiophyceae Phaeocystales Phaeocystaceae Phaeocystis 0.9075226 35 11.3174383 30 11.3583289 42
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Chaetoceros 0.4402659 35 0.1147767 26 6.3862893 36
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Thalassiosira 3.3122191 35 4.1585252 30 2.0747449 33
Ochrophyta Bacillariophyta Bacillariophyta_X Radial-centric-basal-Coscinodiscophyceae Corethron 0.2213539 35 0.0290473 22 0.0005730 1
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Fragilariopsis 4.2573586 35 1.1061643 30 6.7734485 42
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Pseudo-nitzschia 0.0740442 26 0.0503631 19 0.0411637 9
Ochrophyta Bolidophyceae Parmales Triparmaceae Triparma 0.1786538 35 0.2104522 30 0.5277311 28
Ochrophyta Dictyochophyceae Dictyochophyceae_X Florenciellales Florenciella 0.0539616 30 0.0021032 4 0.0109493 9
Ochrophyta Phaeophyceae Phaeophyceae_X Phaeophyceae_XX Ectocarpus 0.0193789 1 0.0004854 2 0.0031598 2
Genera only found in one type of sample
18S filter
division class order family genus n_reads_18S_filter n_samples_18S_filter n_reads_16S_plastid n_samples_16S_plastid n_reads_18S_sort n_samples_18S_sort
Chlorophyta Chlorophyceae Chaetopeltidales Chaetopeltidaceae Planophila 0.0003221 1 NA NA NA NA
Chlorophyta Chlorophyceae Chlamydomonadales Chlamydomonadales_X Haematococcus 0.0001602 1 NA NA NA NA
Chlorophyta Chlorophyceae Chlamydomonadales Chlamydomonadales_X Pleurastrum 0.0009742 3 NA NA NA NA
Chlorophyta Trebouxiophyceae Prasiolales Prasiolales_X Desmococcus 0.0000585 1 NA NA NA NA
Chlorophyta Trebouxiophyceae Watanabea-Clade Watanabea-Clade_X Chloroidium 0.0001530 1 NA NA NA NA
Chlorophyta Ulvophyceae Ulotrichales Ulotrichales_X Chlorothrix 0.0018758 2 NA NA NA NA
Chlorophyta Ulvophyceae Ulvales-relatives Ulvales-relatives_X Dilabifilum 0.0002731 1 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Araphid-pennate Licmophora 0.0007432 1 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Araphid-pennate Pteroncola 0.0007406 4 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Araphid-pennate Thalassionema 0.0011473 2 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Eucampia 0.0005297 3 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Hemiaulus 0.0001122 1 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Shionodiscus 0.0173100 2 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Radial-centric-basal-Coscinodiscophyceae Actinocyclus 0.0017113 4 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Radial-centric-basal-Coscinodiscophyceae Rhizosolenia 0.0000685 1 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Radial-centric-basal-Coscinodiscophyceae Stellarima 0.0001769 1 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Amphora 0.0057413 2 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Cylindrotheca 0.0002630 1 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Cymbella 0.0041439 12 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Encyonema 0.0016080 7 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Haslea 0.0011842 4 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Navicula 0.0008911 4 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Nitzschia 0.0002409 2 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Pauliella 0.0002738 1 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Pleurosigma 0.0011815 3 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Pseudogomphonema 0.0059704 11 NA NA NA NA
Ochrophyta Bolidophyceae Parmales Parmales_env_3 Parmales_env_3A 0.0120071 10 NA NA NA NA
Ochrophyta Chrysophyceae Chrysophyceae_X Chrysophyceae_Clade-C Spumella 0.0144543 5 NA NA NA NA
Ochrophyta Chrysophyceae Chrysophyceae_X Chrysophyceae_Clade-F Paraphysomonas 0.0026271 5 NA NA NA NA
Ochrophyta Dictyochophyceae Dictyochophyceae_X Pedinellales Pseudopedinella 0.0001042 1 NA NA NA NA
Ochrophyta Phaeophyceae Phaeophyceae_X Phaeophyceae_XX Pylaiella 0.0005950 1 NA NA NA NA
Rhodophyta Florideophyceae Ceramiales Delesseriaceae Hemineura 0.0000743 1 NA NA NA NA
Rhodophyta Florideophyceae Ceramiales Delesseriaceae Phycodrys 0.0000850 1 NA NA NA NA
Rhodophyta Florideophyceae Corallinales Corallinales_X Hapalidiaceae 0.0003964 1 NA NA NA NA
Rhodophyta Florideophyceae Corallinales Corallinales_X Mesophyllum 0.0267372 24 NA NA NA NA
Rhodophyta Florideophyceae Corallinales Corallinales_X Synarthrophyton 0.0007191 2 NA NA NA NA
Rhodophyta Florideophyceae Gigartinales Gigartinales_X Stenogramme 0.0015735 2 NA NA NA NA
Rhodophyta Florideophyceae Gracilariales Gracilariales_X Curdiea 0.0011262 4 NA NA NA NA
Rhodophyta Florideophyceae Halymeniales Halymeniales_X Pachymenia 0.0000991 1 NA NA NA NA
Rhodophyta Florideophyceae Plocamiales Plocamiales_X Trematocarpus 0.0004336 2 NA NA NA NA
18S sort
division class order family genus n_reads_18S_filter n_samples_18S_filter n_reads_16S_plastid n_samples_16S_plastid n_reads_18S_sort n_samples_18S_sort
Chlorophyta Ulvophyceae Ulotrichales Ulotrichales_X Ulothrix NA NA NA NA 0.0014895 1
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Bacterosira NA NA NA NA 0.0000804 1
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Skeletonema NA NA NA NA 0.0000463 1
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Bacillaria NA NA NA NA 0.0002977 1
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Luka_AeN707 NA NA NA NA 0.0016083 3
Ochrophyta Pelagophyceae Pelagomonadales Pelagomonadaceae Pelagomonadaceae_clade_A NA NA NA NA 0.0010176 2
Ochrophyta Pelagophyceae Sarcinochrysidales Sarcinochrysidaceae Ankylochrysis NA NA NA NA 0.0000885 1
Ochrophyta Pelagophyceae Sarcinochrysidales Sarcinochrysidaceae Sarcinochrysis NA NA NA NA 0.0000491 1
16S filter
division class order family genus n_reads_18S_filter n_samples_18S_filter n_reads_16S_plastid n_samples_16S_plastid n_reads_18S_sort n_samples_18S_sort
Chlorophyta Chlorophyceae Chlamydomonadales Chlamydomonadales_X Oophila NA NA 0.0001469 2 NA NA
Chlorophyta Trebouxiophyceae Chlorellales Chlorellales_X Chlorella NA NA 0.0001729 1 NA NA
Haptophyta Prymnesiophyceae Prymnesiales Prymnesiaceae Dicrateria NA NA 0.0064689 17 NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Conticribra NA NA 0.0001386 1 NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Lauderia NA NA 0.0000594 1 NA NA
Ochrophyta Dictyochophyceae Dictyochophyceae_X Pedinellales Helicopedinella NA NA 0.0073091 5 NA NA
Ochrophyta Dictyochophyceae Dictyochophyceae_X Pedinellales Mesopedinella NA NA 0.0004326 3 NA NA
Ochrophyta Pelagophyceae Pelagomonadales Pelagomonadaceae Aureococcus NA NA 0.4848461 30 NA NA
Rhodophyta Florideophyceae Ahnfeltiales Ahnfeltiaceae Ahnfeltia NA NA 0.0001100 1 NA NA

Comparison of genera found in the different fractions for 18S filter and 18S sorted

Compute table of number of samples for each genus (rows) vs the three fractions (columns)

  • Only keep
    • 2015 samples because it is the only dataset for which we have the three types of samples
    • Genera that do not contain _X
division class > 20 um 0.2-3 um 3-20 um nano pico
Chlorophyta Chlorophyceae 7 5 5 1 NA
Chlorophyta Mamiellophyceae 17 18 17 18 22
Chlorophyta Palmophyllophyceae 4 15 16 1 1
Chlorophyta Pyramimonadophyceae 18 18 17 19 4
Chlorophyta Trebouxiophyceae 4 NA 3 NA NA
Chlorophyta Ulvophyceae 14 11 13 2 2
Cryptophyta Cryptophyceae 19 18 17 22 9
Haptophyta Prymnesiophyceae 19 18 17 22 22
Ochrophyta Bacillariophyta 19 18 17 22 22
Ochrophyta Bolidophyceae 19 18 17 21 20
Ochrophyta Chrysophyceae 14 17 17 2 2
Ochrophyta Dictyochophyceae 11 18 17 15 1
Ochrophyta MOCH-2 10 13 15 11 NA
Ochrophyta Pelagophyceae 19 18 17 22 22
Ochrophyta Phaeophyceae 19 12 17 10 NA
Rhodophyta Florideophyceae 18 13 16 NA NA
division class order family genus > 20 um 0.2-3 um 3-20 um nano pico
Chlorophyta Chlorophyceae Chlamydomonadales Chlamydomonadales_X Chlamydomonas 6 4 3 1 NA
Chlorophyta Chlorophyceae Chlamydomonadales Chlamydomonadales_X Pleurastrum 1 1 2 NA NA
Chlorophyta Chlorophyceae Sphaeropleales Sphaeropleales_X Radiococcus 1 NA NA NA NA
Chlorophyta Mamiellophyceae Dolichomastigales Dolichomastigaceae Dolichomastigaceae-B 12 18 17 1 5
Chlorophyta Mamiellophyceae Mamiellales Bathycoccaceae Bathycoccus 5 17 15 1 22
Chlorophyta Mamiellophyceae Mamiellales Mamiellaceae Micromonas 17 17 17 17 22
Chlorophyta Palmophyllophyceae Prasinococcales Prasinococcales-Clade-B Prasinoderma 4 15 16 1 1
Chlorophyta Pyramimonadophyceae Pyramimonadales Pyramimonadaceae Pyramimonas 18 18 17 19 4
Chlorophyta Trebouxiophyceae Chlorellales Chlorellales_X Chlorella 1 NA NA NA NA
Chlorophyta Ulvophyceae Ulotrichales Ulotrichales_X Chlorothrix 4 NA 2 NA NA
Chlorophyta Ulvophyceae Ulotrichales Ulotrichales_X Monostroma 10 9 10 2 1
Chlorophyta Ulvophyceae Ulotrichales Ulotrichales_X Ulothrix 2 NA NA 1 NA
Chlorophyta Ulvophyceae Ulvales-relatives Ulvales-relatives_X Acrochaete 2 3 6 NA 1
Chlorophyta Ulvophyceae Ulvales-relatives Ulvales-relatives_X Dilabifilum 1 1 NA NA NA
Cryptophyta Cryptophyceae Cryptomonadales Cryptomonadales_X Geminigera 19 18 17 22 8
Cryptophyta Cryptophyceae Cryptomonadales Cryptomonadales_X Hemiselmis 2 4 3 1 NA
Haptophyta Prymnesiophyceae Phaeocystales Phaeocystaceae Phaeocystis 19 18 17 22 20
Haptophyta Prymnesiophyceae Prymnesiales Chrysochromulinaceae Chrysochromulina 3 9 9 22 5
Ochrophyta Bacillariophyta Bacillariophyta_X Araphid-pennate Asteroplanus 19 18 17 20 3
Ochrophyta Bacillariophyta Bacillariophyta_X Araphid-pennate Grammonema 2 NA 3 NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Araphid-pennate Licmophora 7 1 NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Araphid-pennate Pteroncola 7 1 3 NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Araphid-pennate Synedra 2 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Araphid-pennate Synedropsis 1 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Araphid-pennate Tabularia 1 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Araphid-pennate Thalassiothrix 1 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Chaetoceros 19 18 17 16 20
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Eucampia 2 2 1 NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Minidiscus 19 18 17 22 10
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Odontella 3 NA 1 NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Porosira 19 18 17 2 1
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Shionodiscus 12 2 NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Thalassiosira 19 18 17 21 12
Ochrophyta Bacillariophyta Bacillariophyta_X Radial-centric-basal-Coscinodiscophyceae Actinocyclus 11 2 2 NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Radial-centric-basal-Coscinodiscophyceae Corethron 19 18 17 NA 1
Ochrophyta Bacillariophyta Bacillariophyta_X Radial-centric-basal-Coscinodiscophyceae Proboscia 7 5 8 NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Radial-centric-basal-Coscinodiscophyceae Rhizosolenia 2 1 NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Radial-centric-basal-Coscinodiscophyceae Stellarima 3 1 NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Achnanthes 1 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Amphora 12 2 NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Cocconeis 1 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Cymbella 10 3 9 NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Dickieia 4 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Encyonema 6 1 6 NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Fragilariopsis 19 18 17 22 20
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Gyrosigma 1 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Haslea 3 2 2 NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Navicula 5 2 2 NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Naviculales 4 8 11 4 2
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Pinnularia 1 NA NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Pleurosigma 3 1 2 NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Pseudo-nitzschia 15 10 16 7 2
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Pseudogomphonema 10 5 6 NA NA
Ochrophyta Bolidophyceae Parmales Parmales_env_3 Parmales_env_3A 2 10 NA NA NA
Ochrophyta Bolidophyceae Parmales Parmales_env_3 Parmales_env_3B 17 18 17 21 15
Ochrophyta Bolidophyceae Parmales Triparmaceae Triparma 19 18 17 11 17
Ochrophyta Chrysophyceae Chrysophyceae_X Chrysophyceae_Clade-F Paraphysomonas 1 3 2 NA NA
Ochrophyta Dictyochophyceae Dictyochophyceae_X Dictyochales Dictyocha 1 NA NA NA NA
Ochrophyta Dictyochophyceae Dictyochophyceae_X Florenciellales Florenciella 7 15 15 9 NA
Ochrophyta Dictyochophyceae Dictyochophyceae_X Florenciellales Pseudochattonella 7 13 16 9 NA
Ochrophyta Pelagophyceae Pelagomonadales Pelagomonadaceae Pelagomonas 3 11 4 3 18
Ochrophyta Phaeophyceae Phaeophyceae_X Phaeophyceae_XX Desmarestia 18 8 16 5 NA
Ochrophyta Phaeophyceae Phaeophyceae_X Phaeophyceae_XX Ectocarpus 4 NA 1 2 NA
Ochrophyta Phaeophyceae Phaeophyceae_X Phaeophyceae_XX Phaeurus 16 9 15 7 NA
Ochrophyta Phaeophyceae Phaeophyceae_X Phaeophyceae_XX Pylaiella 1 NA 1 NA NA
Rhodophyta Florideophyceae Ceramiales Callithamniaceae Diapse 1 NA NA NA NA
Rhodophyta Florideophyceae Ceramiales Delesseriaceae Phycodrys 4 NA 1 NA NA
Rhodophyta Florideophyceae Ceramiales Sarcomeniaceae Platysiphonia 1 NA NA NA NA
Rhodophyta Florideophyceae Colaconematales Colaconematales_X Palmaria 1 3 3 NA NA
Rhodophyta Florideophyceae Corallinales Corallinales_X Hapalidiaceae 6 1 NA NA NA
Rhodophyta Florideophyceae Corallinales Corallinales_X Mesophyllum 17 10 14 NA NA
Rhodophyta Florideophyceae Corallinales Corallinales_X Synarthrophyton 8 1 1 NA NA
Rhodophyta Florideophyceae Gigartinales Gigartinales_X Chondrus 18 7 16 NA NA
Rhodophyta Florideophyceae Gigartinales Gigartinales_X Schottera 1 NA NA NA NA
Rhodophyta Florideophyceae Gigartinales Gigartinales_X Stenogramme 3 NA 2 NA NA
Rhodophyta Florideophyceae Gracilariales Gracilariales_X Curdiea 7 1 3 NA NA
Rhodophyta Florideophyceae Plocamiales Plocamiales_X Trematocarpus 7 1 1 NA NA
Chlorophyta Chlorophyceae Chaetopeltidales Chaetopeltidaceae Planophila NA 1 NA NA NA
Chlorophyta Chlorophyceae Chlamydomonadales Chlamydomonadales_X Haematococcus NA 1 NA NA NA
Chlorophyta Mamiellophyceae Mamiellales Mamiellaceae Mantoniella NA 1 NA 1 NA
Cryptophyta Cryptophyceae Cryptomonadales Cryptomonadales_X Teleaulax NA 1 NA NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Araphid-pennate Thalassionema NA 1 1 NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Nitzschia NA 1 1 NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Pauliella NA 1 NA NA NA
Ochrophyta Chrysophyceae Chrysophyceae_X Chrysophyceae_Clade-C Spumella NA 5 NA NA NA
Ochrophyta Dictyochophyceae Dictyochophyceae_X Pedinellales Pseudopedinella NA 1 NA NA NA
Rhodophyta Florideophyceae Ceramiales Delesseriaceae Hemineura NA 1 NA NA NA
Rhodophyta Florideophyceae Halymeniales Halymeniales_X Pachymenia NA 1 NA NA NA
Chlorophyta Trebouxiophyceae Prasiolales Prasiolales_X Desmococcus NA NA 1 NA NA
Chlorophyta Trebouxiophyceae Watanabea-Clade Watanabea-Clade_X Chloroidium NA NA 1 NA NA
Cryptophyta Cryptophyceae Cryptomonadales Cryptomonadales_X Falcomonas NA NA 2 3 1
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Hemiaulus NA NA 1 NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Cylindrotheca NA NA 1 NA NA
Ochrophyta Phaeophyceae Phaeophyceae_X Phaeophyceae_XX Saccharina NA NA 1 NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Bacterosira NA NA NA 1 NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Bacillaria NA NA NA 1 NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Luka_AeN707 NA NA NA 2 1
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Skeletonema NA NA NA NA 1
Ochrophyta Pelagophyceae Pelagomonadales Pelagomonadaceae Pelagomonadaceae_clade_A NA NA NA NA 2
Ochrophyta Pelagophyceae Sarcinochrysidales Sarcinochrysidaceae Ankylochrysis NA NA NA NA 1
Ochrophyta Pelagophyceae Sarcinochrysidales Sarcinochrysidaceae Sarcinochrysis NA NA NA NA 1

Comparison of genera found in the different fractions for 18S filter

Compute table of number of samples for each genus (rows) vs the three fractions (columns)

  • Only keep
    • Genera that do not contain _X
  • We consider now ALL samples (will need to remove samples for which the > 20 um is missing)
division class > 20 um 0.2-3 um 3-20 um
Chlorophyta Chlorophyceae 8 6 6
Chlorophyta Mamiellophyceae 31 43 44
Chlorophyta Palmophyllophyceae 5 26 25
Chlorophyta Pyramimonadophyceae 29 39 44
Chlorophyta Trebouxiophyceae 9 1 7
Chlorophyta Ulvophyceae 29 27 29
Cryptophyta Cryptophyceae 36 43 44
Haptophyta Prymnesiophyceae 33 43 43
Ochrophyta Bacillariophyta 36 43 44
Ochrophyta Bolidophyceae 35 43 44
Ochrophyta Chrysophyceae 29 42 42
Ochrophyta Dictyochophyceae 28 43 44
Ochrophyta MOCH-1 1 3 4
Ochrophyta MOCH-2 15 24 36
Ochrophyta Pelagophyceae 35 43 44
Ochrophyta Phaeophyceae 34 34 43
Ochrophyta Xanthophyceae 1 NA NA
Rhodophyta Bangiophyceae 2 1 NA
Rhodophyta Florideophyceae 35 37 43
division class order family genus > 20 um 0.2-3 um 3-20 um
Chlorophyta Chlorophyceae Chlamydomonadales Chlamydomonadales_X Chlamydomonas 7 4 4
Chlorophyta Chlorophyceae Chlamydomonadales Chlamydomonadales_X Pleurastrum 1 1 2
Chlorophyta Chlorophyceae Sphaeropleales Sphaeropleales_X Radiococcus 1 NA NA
Chlorophyta Mamiellophyceae Dolichomastigales Dolichomastigaceae Dolichomastigaceae-B 15 26 27
Chlorophyta Mamiellophyceae Mamiellales Bathycoccaceae Bathycoccus 14 41 41
Chlorophyta Mamiellophyceae Mamiellales Mamiellaceae Micromonas 27 42 41
Chlorophyta Palmophyllophyceae Prasinococcales Prasinococcales-Clade-B Prasinoderma 5 26 25
Chlorophyta Pyramimonadophyceae Pyramimonadales Pyramimonadaceae Pyramimonas 29 39 44
Chlorophyta Trebouxiophyceae Chlorellales Chlorellales_X Chlorella 1 NA NA
Chlorophyta Trebouxiophyceae Prasiolales Prasiolales_X Koliella 1 NA NA
Chlorophyta Trebouxiophyceae Watanabea-Clade Watanabea-Clade_X Chloroidium 2 1 2
Chlorophyta Ulvophyceae Ulotrichales Ulotrichales_X Chlorothrix 16 5 8
Chlorophyta Ulvophyceae Ulotrichales Ulotrichales_X Monostroma 12 11 14
Chlorophyta Ulvophyceae Ulotrichales Ulotrichales_X Ulothrix 2 2 1
Chlorophyta Ulvophyceae Ulvales-relatives Ulvales-relatives_X Acrochaete 5 8 13
Chlorophyta Ulvophyceae Ulvales-relatives Ulvales-relatives_X Dilabifilum 3 5 5
Cryptophyta Cryptophyceae Cryptomonadales Cryptomonadales_X Geminigera 36 43 44
Cryptophyta Cryptophyceae Cryptomonadales Cryptomonadales_X Hemiselmis 2 7 7
Haptophyta Prymnesiophyceae Phaeocystales Phaeocystaceae Phaeocystis 33 43 43
Haptophyta Prymnesiophyceae Prymnesiales Chrysochromulinaceae Chrysochromulina 6 23 31
Ochrophyta Bacillariophyta Bacillariophyta_X Araphid-pennate Asteroplanus 35 39 43
Ochrophyta Bacillariophyta Bacillariophyta_X Araphid-pennate Grammonema 9 2 8
Ochrophyta Bacillariophyta Bacillariophyta_X Araphid-pennate Licmophora 17 1 1
Ochrophyta Bacillariophyta Bacillariophyta_X Araphid-pennate Pteroncola 8 1 4
Ochrophyta Bacillariophyta Bacillariophyta_X Araphid-pennate Synedra 2 1 NA
Ochrophyta Bacillariophyta Bacillariophyta_X Araphid-pennate Synedropsis 1 NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Araphid-pennate Tabularia 1 NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Araphid-pennate Thalassionema 2 1 2
Ochrophyta Bacillariophyta Bacillariophyta_X Araphid-pennate Thalassiothrix 4 2 3
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Chaetoceros 36 42 43
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Ditylum 2 1 1
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Eucampia 14 14 11
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Hemiaulus 3 3 6
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Minidiscus 36 42 44
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Odontella 6 NA 1
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Porosira 36 43 42
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Shionodiscus 20 3 4
Ochrophyta Bacillariophyta Bacillariophyta_X Polar-centric-Mediophyceae Thalassiosira 35 43 44
Ochrophyta Bacillariophyta Bacillariophyta_X Radial-centric-basal-Coscinodiscophyceae Actinocyclus 24 7 5
Ochrophyta Bacillariophyta Bacillariophyta_X Radial-centric-basal-Coscinodiscophyceae Asteromphalus 2 NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Radial-centric-basal-Coscinodiscophyceae Corethron 36 42 43
Ochrophyta Bacillariophyta Bacillariophyta_X Radial-centric-basal-Coscinodiscophyceae Coscinodiscus 2 NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Radial-centric-basal-Coscinodiscophyceae Guinardia 1 1 3
Ochrophyta Bacillariophyta Bacillariophyta_X Radial-centric-basal-Coscinodiscophyceae Proboscia 19 12 23
Ochrophyta Bacillariophyta Bacillariophyta_X Radial-centric-basal-Coscinodiscophyceae Rhizosolenia 3 1 2
Ochrophyta Bacillariophyta Bacillariophyta_X Radial-centric-basal-Coscinodiscophyceae Stellarima 10 4 2
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Achnanthes 3 NA 2
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Amphora 18 3 3
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Cocconeis 1 1 NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Cymbella 14 7 21
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Dickieia 4 1 1
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Encyonema 12 4 8
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Fragilariopsis 36 43 44
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Gyrosigma 1 NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Haslea 11 12 14
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Navicula 12 7 10
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Naviculales 4 11 15
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Pinnularia 1 NA NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Pleurosigma 3 1 2
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Pseudo-nitzschia 30 22 32
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Pseudogomphonema 12 6 7
Ochrophyta Bolidophyceae Parmales Parmales_env_3 Parmales_env_3A 5 28 12
Ochrophyta Bolidophyceae Parmales Parmales_env_3 Parmales_env_3B 29 42 42
Ochrophyta Bolidophyceae Parmales Triparmaceae Triparma 35 43 44
Ochrophyta Chrysophyceae Chrysophyceae_X Chrysophyceae_Clade-C Pedospumella 1 1 NA
Ochrophyta Chrysophyceae Chrysophyceae_X Chrysophyceae_Clade-C Spumella 2 13 7
Ochrophyta Chrysophyceae Chrysophyceae_X Chrysophyceae_Clade-F Paraphysomonas 4 12 7
Ochrophyta Dictyochophyceae Dictyochophyceae_X Dictyochales Dictyocha 2 5 4
Ochrophyta Dictyochophyceae Dictyochophyceae_X Florenciellales Florenciella 13 38 41
Ochrophyta Dictyochophyceae Dictyochophyceae_X Florenciellales Pseudochattonella 11 34 43
Ochrophyta Pelagophyceae Pelagomonadales Pelagomonadaceae Pelagomonas 6 28 16
Ochrophyta Phaeophyceae Phaeophyceae_X Phaeophyceae_XX Desmarestia 30 25 35
Ochrophyta Phaeophyceae Phaeophyceae_X Phaeophyceae_XX Ectocarpus 8 2 3
Ochrophyta Phaeophyceae Phaeophyceae_X Phaeophyceae_XX Phaeurus 28 10 21
Ochrophyta Phaeophyceae Phaeophyceae_X Phaeophyceae_XX Pylaiella 4 NA 2
Ochrophyta Phaeophyceae Phaeophyceae_X Phaeophyceae_XX Saccharina 1 2 6
Ochrophyta Xanthophyceae Xanthophyceae_X Xanthophyceae_XX Botrydiopsis 1 NA NA
Rhodophyta Bangiophyceae Bangiales Bangiaceae Porphyra 1 NA NA
Rhodophyta Bangiophyceae Bangiales Bangiaceae Pyropia 1 1 NA
Rhodophyta Florideophyceae Ceramiales Callithamniaceae Diapse 2 1 NA
Rhodophyta Florideophyceae Ceramiales Delesseriaceae Phycodrys 7 2 7
Rhodophyta Florideophyceae Ceramiales Sarcomeniaceae Platysiphonia 1 1 NA
Rhodophyta Florideophyceae Colaconematales Colaconematales_X Palmaria 14 18 18
Rhodophyta Florideophyceae Corallinales Corallinales_X Hapalidiaceae 7 2 1
Rhodophyta Florideophyceae Corallinales Corallinales_X Mesophyllum 32 22 36
Rhodophyta Florideophyceae Corallinales Corallinales_X Synarthrophyton 11 2 1
Rhodophyta Florideophyceae Gigartinales Gigartinales_X Chondrus 34 22 41
Rhodophyta Florideophyceae Gigartinales Gigartinales_X Schottera 1 NA NA
Rhodophyta Florideophyceae Gigartinales Gigartinales_X Stenogramme 4 NA 2
Rhodophyta Florideophyceae Gracilariales Gracilariales_X Curdiea 14 4 9
Rhodophyta Florideophyceae Plocamiales Plocamiales_X Trematocarpus 10 1 1
Chlorophyta Chlorophyceae Chaetopeltidales Chaetopeltidaceae Planophila NA 1 NA
Chlorophyta Chlorophyceae Chlamydomonadales Chlamydomonadales_X Haematococcus NA 1 NA
Chlorophyta Mamiellophyceae Mamiellales Mamiellaceae Mantoniella NA 4 1
Cryptophyta Cryptophyceae Cryptomonadales Cryptomonadales_X Plagioselmis NA 1 1
Cryptophyta Cryptophyceae Cryptomonadales Cryptomonadales_X Teleaulax NA 1 NA
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Nitzschia NA 1 1
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Pauliella NA 1 1
Ochrophyta Dictyochophyceae Dictyochophyceae_X Pedinellales Pseudopedinella NA 1 2
Ochrophyta Dictyochophyceae Dictyochophyceae_X Pedinellales Pteridomonas NA 1 NA
Rhodophyta Florideophyceae Ceramiales Dasyaceae Dasya NA 1 NA
Rhodophyta Florideophyceae Ceramiales Delesseriaceae Hemineura NA 1 NA
Rhodophyta Florideophyceae Ceramiales Rhodomelaceae Rhodomela NA 1 1
Rhodophyta Florideophyceae Gigartinales Gigartinales_X Kallymenia NA 1 2
Rhodophyta Florideophyceae Halymeniales Halymeniales_X Pachymenia NA 1 NA
Chlorophyta Trebouxiophyceae Prasiolales Prasiolales_X Desmococcus NA NA 1
Chlorophyta Trebouxiophyceae Prasiolales Prasiolales_X Prasiola NA NA 3
Cryptophyta Cryptophyceae Cryptomonadales Cryptomonadales_X Falcomonas NA NA 2
Ochrophyta Bacillariophyta Bacillariophyta_X Raphid-pennate Cylindrotheca NA NA 1
Rhodophyta Florideophyceae Gigartinales Gigartinales_X Delisea NA NA 1

Figures

CARBOM code

2019-10-18